The present invention, in some embodiments thereof, relates to a positioning technique and, more particularly, but not exclusively, to a method and system for estimating a position in a multipath environment.
Locating a target in a wireless system involves the collection of location information from radio signals propagating between the target and a number of base stations at known position.
The ability to determine the location or position of a wireless device has become increasingly desirable as an ever increasing number of people carry wireless devices, such as mobile phones, pagers, wireless email/Internet devices, and communications radios on a daily basis. In most cases, because individuals carry the wireless devices on or about their person, it is a reasonable assumption that the position of a particular wireless device is also that of its owner. As a result, locating an individual may be accomplished by locating the wireless device they carry.
With the proliferation of private and public Wi-Fi networks in recent years, several positioning systems based on Wi-Fi networks have been introduced. In a wide-area Wi-Fi positioning system, the location and characteristics of Wi-Fi access points are used to locate Wi-Fi enabled mobile devices.
Time of arrival (TOA) based positioning techniques rely on measuring the propagation times between the target and the base stations. These measurements are based on estimation of the first arrival time of the transmitted signal. In case of multipath channel, where the transmitted signal is reflected by objects, walls, cars, buildings, people etc., the received signal contains several overlapping replicas of the transmitted signal and with the addition of noise accurate estimation of the first arrival time is a considerable challenge.
TOA estimation methods based on passing the received signal through a matched filter (MF) whose output peak epoch is the TOA estimate are disclosed in W. Chung and D. Ha, “An accurate ultra wideband (UWB) ranging for precision asset location,” in Proc. IEEE Conf. Ultrawideband Syst. Technol. (UWBST), Reston, Va., November 2003, pp. 389-393; and K. Yu and I. Oppermann, “Performance of UWB position estimation based on time-of-arrival measurements,” in Proc. IEEE Conf. Ultrawideband Syst. Technol. (UWBST), Kyoto, Japan, May 2004, pp. 400-404.
An alternative solution where a search for a finite number of MF output peak epochs is performed and then the TOA is estimated as the earliest peak epoch is disclosed in V. Lottici, A. D'Andrea, and U. Mengali, “Channel estimation for ultrawideband communications,” IEEE J. Select. Areas Commun., vol. 20, no. 9, pp. 1638-1645, December 2002. Other solutions are based on comparing the received signal energy to a threshold and then performing a forward or backwards search with a heuristic TOA estimation criterion [L. Stoica, A. Rabbachin, and I. Oppermann, “A low-complexity noncoherent IR-UWB transceiver architecture with TOA estimation,” IEEE Trans. Microwave Theory Tech., vol. 54, pp. 1637-1646, June 2006; I. Guvenc, Z. Sahinoglu, and P. V. Orlik, “TOA Estimation for IR-UWB Systems With Different Transceiver Types,” IEEE Trans. Microwave Theory and Tech., vol. 54, no. 4, April 2006; D. Dardari, C.-C. Chong, and M. Z. Win, “Analysis of threshold-based TOA estimator in UWB channels,” in Proc. Eur. Signal Process. Conf. (EUSIPCO), Florence, Italy, September 2006; A. Chehri, P. Fortier and P. M. Tardif, “Time-of-Arrival Estimation For IR-UWB Systems Based on Two Step Energy Detection” Biennial Symposium on Commun., pp. 369-373, June 2008.
Other approaches include the “frequency-domain super-resolution TOA estimation” which includes Multiple Signal Classification (MUSIC) [X. Li, “Super-Resolution TOA Estimation With Diversity for Indoor Geolocation,” IEEE Trans. Wireless Commun., vol. 3, no. 1, January 2004], Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) [R. Roy, A. Paulraj and T. Kailath, “Estimation of Signal Parameters via Rotational Invariance Techniques-ESPRIT”, IEEE Trans. Acoust., Speech, Signal Process., vol. 37, no. 7, pp. 984-995, July 1989.] and other algorithms [R. J. J. Vidal, M. Najar, “High resolution time-of-arrival detection for wireless positioning systems”, In IEEE Vehicular Technology Conference, Vancouver, Canada, pp. 2283-2287, September 2002; M. Navarro and M. Najar, “Joint Estimation of TOA and DOA in IR-UWB”, IEEE Workshop on Signal Processing Advances in Wireless Commun., Helsinki, Finland, pp. 17-20, June 2007]. Win and Scholtz [M. Z. Win and R. A. Scholtz, “Characterization of ultra-wide bandwidth wireless indoor communications channels: A communication theoretic view,” IEEE J. Sel. Areas Commun., vol. 20, pp. 1613-1627, December 2002] introduced the generalized maximum likelihood (GML) solution. The method relies on the assumption that the number of multipath components is finite and known and all the multipath coefficients and their arrival times are jointly estimated.
An iterative approximation to the GML was introduced by [J. Y. Lee and R. A. Scholtz, “Ranging in a dense multipath environment using an UWB radio link,” IEEE J. Select. Areas Commun, vol. 20, no. 9, pp. 1677-1683, December 2002.]. The multipath coefficients are estimated one by one and removed from the received signal sequentially until the strongest remaining coefficient is below a preset threshold. The TOA is determined according to the earliest arrival path.
European Publication No. EP1596217 discloses a method of detecting the time of arrival (TOA) of the first-arrival-path signal in a transmission system where wide band signals are transmitted. A parameter related to the energy of a plurality of samples of a received signal resulting from a multipath propagation of a transmitted signal is evaluated. For each TOA candidate sample, the observation period is divided into a corresponding pair of complementary windows, where the first window in each pair comprises the samples preceding the candidate sample and the other one comprises the remaining samples in the period. The signal energy in both windows of each window pair is evaluated, and the sample giving rise to windows whose energies maximize a function related to the energy ratio of the two windows in each pair is chosen as the estimated TOA sample.
Additional background art includes I. Guvenc and C. C. Chong, “A Survey on TOA Based Wireless Location and NLOS Mitigation Techniques”, IEEE Comm. Surveys and Tutorials, vol. 11, no. 3, pp. 107-124, 2009; K. W. K. Lui, H. C. So and W. K. Ma, “Maximum A Posteriori Approach to Time-of-Arrival-Based Localization in Non-Line-of-Sight Environment”, IEEE Trans. on Vehicular Technology, vol. 53, no. 3, pp. 1517-1523, Match 2010; P. C. Chen, “A non-line-of-sight error mitigation algorithm in location estimation”, in Proc. IEEE Int. Conf. Wireless Commun. Netw. (WCNC), vol. 1, pp. 316-320, September 1999; A. Al-Jazzar and J. J. Caffery, “ML and Bayesian TOA location estimators for NLOS environments”, in Proc. IEEE Veh. Technol. Conf. (VTS), vol. 2, pp. 1178-1181, September 2002; Y. T. Chan, H. Y. Chin Hang and Pak-chung Ching, “Exact and Approximate Maximum Likelihood Localization Algorithms”, IEEE Trans. on Vehicular Technology, vol. 55, no. 1, pp. 10-16, January 2006; S. Gezici and H. V. Poor “Position Estimation via Ultra-Wide-Band Signals”, Proceeding of the IEEE, vol. 97, no. 2, pp. 386-403, February 2009; A. J. Weiss, “Direct Position Determination of Narrowband Radio Frequency Transmitters”, IEEE Signal Processing Letters, vol. 11, no. 5, May 2004; P. Closas, C. Fernandez-Prades and J. A. Fernandez-Rubio, “Maximum Likelihood Estimation of Position in GNSS”, IEEE Signal Processing Letters, vol. 14, no. 5, May 2007; P. Closas, C. Fernandez-Prades and J. A. Fernandez-Rubio, “Cramer-Rao Bound Analysis of Positioning Approaches in GNSS Receivers”, IEEE Transactions On Signal Processing, vol. 57, no. 10, October 2009; P. Closas, C. Fernandez-Prades, D. Bernal and J. A. Fernandez-Rubio, “Bayesian Direct Position Estimation”, IEEE Aerospace Conference, 2010; C. Yen and P. J. Voltz, “Indoor positioning based on statistical multipath channel modeling,” EURASIP Journal on Wireless Communications and Networking 2011; K. Papakonstantinou and D. Slock, “Direct Location Estimation for MIMO Systems in Multipath Environments”, IEEE Global Communications Conference (GLOBECOM). November 2008; and M. Eric and D. Vucic, “Direct position estimation of UWB transmitters in multipath conditions”, IEEE International Conference on Ultra-Wideband (ICUWB 2008), vol. 1. 2008.